Sandeep Chanda Portfolio

Data Analyst with 5+ years of experience in transforming complex data into actionable insights to drive strategic business decisions. Skilled in SQL, AWS, Python, Tableau and Microsoft Office Suite with a strong focus on data quality assurance, trend analysis and process optimization. Proven ability to collaborate with cross-functional teams, develop benchmarks and implement automation leading to measurable improvements in operational efficiency
GitHubProfile:@sandeepchanda

Excel Project
Climate Change Analysis

The Climate Change Analysis Project aims to address the urgent issue of climate change through comprehensive analysis. In the project i had used analytical tools like forecasting and regression to study and mitigate climate change. It highlights the urgent need to address rising CO2 emissions and recommends strategies for emission reduction and promoting renewable energy. Key findings emphasize significant differences among energy sources, providing critical insights for policymakers to develop effective climate policies.

Decision Tree Project

The main objective of the project is to analyze predictors for oatmeal preference using decision trees. The analysis identified age as the most significant predictor, followed by exercise, marital status, and gender. The model's performance was evaluated using confusion matrices for both training and validation datasets, showing moderate overall accuracy. Recommendations for promoting oatmeal sales include targeted ads for different age groups and highlighting health benefits. The project also includes a decision tree graphic created in RStudio and associated R code for analysis.

Descriptive Analysis Project

The project involves a comprehensive descriptive analysis of sales data, focusing on key metrics such as cycle time, sales, and profit across various sub-categories and segments. The analysis highlights areas of strength (e.g., copiers) and areas needing improvement (e.g., machines and tables). The consumer segment has the highest sales but also a loss, whereas the home office segment shows better profitability. The project provides valuable insights into sales and profit performance across different sub-categories and segments.